Noninvasive imaging of cardiac electrical activity inside the human body has historically been a challenge. A significant amount of effort has been put forth in past decades in the development of high-resolution cardiac electric imaging techniques, which attempt to image myocardial electrical activity without ad hoc assumption on the number of sources. Due to the high temporal resolution inherent in the bioelectromagnetic measurements such as electrocardiogram and magnetocardiogram, the availability of bioelectromagnetic source imaging modalities provides much needed high temporal resolution in mapping the functional status of the heart, and aiding clinical diagnosis and treatment of cardiac abnormalities, such as guiding catheter ablation of cardiac arrhythmias.
Attempts have been made to mathematically reconstruct the equivalent source distribution of cardiac bioelectric activity. The choice of equivalent cardiac source determines what kind of information that may be deduced concerning cardiac electrical source distribution. Savard et al. has approximate cardiac electrical activity by a single equivalent current dipole which can move within the myocardium, see “Representation of cardiac electrical activity by a moving dipole for normal and ectopic beats in the intact dog,” Circulation Research, 425, 1980. However, Savard et al.'s approach did not provide a means of imaging distributed cardiac electrical activity but a single equivalent dipole. Mirvis et al. has attempted to localize multiple epicardial events using a two-dipole technique, see “Detection and localization of multiple epicardial electrical generators by a two-dipole ranging technique,” Circulation Research, 551, 1977. However, Mirvis et al.'s approach also did not provide a means of imaging distributed cardiac electrical activity but only two discrete point sources within the heart. In an attempt to image distributed cardiac electrical activity, Barr et al. used the electrical potential over the outer surface of the heart as an equivalent source model, see “Relating epicardial to body surface potential distributions by means of transfer coefficients based on geometry measurements,” IEEE Transactions on Biomedical Engineering, 1, 1977. However, Barr et al.'s approach provided electrical potential distribution over the two dimensional surface of the epicardium. Oster et al has further extended the technique to reconstruct epicardial potentials, electrograms and activation sequence, see “Noninvasive electrocardiographic imaging: reconstruction of epicardial potentials, electrograrns, and isochrones and localization of single and multiple electrocardiac events,” Circulation, 1012, 1997. While Oster et al.'s approach provided activation sequence over the two dimensional surface of the epicardium, it did not provide a means of imaging cardiac activation sequence within the three dimensional volume of the heart. Branham et al. described a system of mapping activation sequence over the epicardial and endocardial surfaces, see U.S. Pat No. 5,687,737. However, these heart surface activation imaging approaches only provided activation sequence over the heart surface, not within the three dimensional volume of the myocardium.
Attempts have also been made to map and localize cardiac electric activity from the endocardium due to rapid development in catheter techniques. Ben-Haim et al. has developed a non-fluorescent electroanatomic catheter mapping technique using electromagnetic guidance of the catheter positioning, see “Nonfluoroscopic in vivo navigation and mapping technology,” Nature Medicine, 1393, 1996. However, due to the multiple sequential positioning and measurement of the potentials, this technique currently does not provide beat-to-beat mapping capability, which is required for guiding catheter ablation of hemodynamically unstable arrhythmia. Khoury et al. has attempted to use a cavitary noncontact multielectrode catheter-probe to record electrical potentials in the blood-filled cavity, and explored inverse reconstruction of endocardial potentials from the potential measurements made on the catheter probe, see “Three-dimensional electrophsyiological imaging of the intact canine left ventricle using a noncontact multielectrode cavitary probe: study of sinus, paced, and spontaneous premature beats,” Circulation, 399, 1998. Beatty et al. described a system mapping electrical activity of the heart from endocardial surface, see U.S. Pat. No. 6,240,307. However, these approaches are invasive techniques, and the estimated electrical potential or activation patterns are over the two dimensional surface of endocardium, not within the three dimensional volume of the heart.
While the heart-surface inverse solutions provide much enhanced spatial resolution regarding the underlying cardiac electrical activity as compared with the smeared body surface (or balloon surface) potential distribution, the heart-surface inverse solutions are still limited in that it is an inverse solution over the surface of the heart, within which the true myocardial electric activity is located over the three-dimensional myocardium. For example, it is desirable to localize sites of origin of cardiac arrhythmia in the three-dimensional myocardium, in order to accurately guide radio-frequency catheter ablation procedures. The information available over the heart surface regarding the underlying myocardial activation will still need to be processed to lead to directly useful information in a clinical setting. There is a need to develop noninvasive techniques to image and localize cardiac electric activity and site of arrhythmias in the three-dimensional myocardium.
Recently attempts have been made to estimate the three-dimensional distribution of current dipoles not in the heart but in the brain through a Laplacian weighted minimum norm solution. See “Low resolution electromagnetic tomography: a new method for localizing electrical activity in the brain,” published by R. D. Pascual-Marqui et al. in Int. J. of Psychophysiology, 49, 1994. See also “The Laplacian weighted minimum norm estimate of three dimensional equivalent charge distribution in the brain,” published by D. Yao and B. He in the Proceedings of the 20th annual international conference of IEEE engineering in medicine and biology society, 2108, 1998. The main advantage of these weighted minimum norm brain-imaging approaches is that knowledge of the source multiplicity is not required, and it may lead to estimates of the source density all throughout the three dimensional volume of the brain. I. F. Gorodnitsky et al. further improved the weighted minimum norm solution for localization of focal neural sources from magnetoencephalogram, using a recursive weighting strategy, see “Neuromagnetic source imaging with FOCUSS: a recursive weighted minimum norm algorithm,” published in Electroencepholography & clinical Neurophysiology, 231, 1995. However, there has been no, to our knowledge, prior art in estimating excitation sequence of neuronal activation within the three-dimensional volume of the brain. Amir et al. described a method and means of estimating brain source generators using a lead-field analysis method in a boundary element model of the head, see U.S. Pat. No. 5,701,909. However, Amir et al. did not show estimating three dimensional activation sequence within the brain. Tucker et al. also described a device of estimating brain electrical source, see U.S. Pat. No. 6,330,470. However, Tucker et al. also did not describe estimation of three dimensional activation sequence within the brain. Jewett et al. showed a device for measuring variations in measured physical parameters of source-generators, see U.S. Pat. No. 5,687,724. However, Jewett et al. also did not determine the activation sequence within the brain. Van Veen et al. described a method of estimating brain electrical sources by filter banks, see U.S. Pat. No. 5,263,488. However, Van Veen et al. also did not show estimating activation sequence within the brain.
To our knowledge, there have been no comprehensive reports to estimate the three-dimensional excitation sequence, three dimensional distribution of electrical source inside the heart from noninvasive electrocardiographic measurements made over the body surface or magnetocardiographic measurements made out of the body. There have been, to our knowledge, no comprehensive reports to estimate the activation sequence within the three dimensional volume of the brain from the electrical signals measured over the surface of the head or magnetoencephalograms measured out of the head. Lu et al attempted to localize the site of preexcitation of WPW syndrome using a model based inverse procedure, see “Extraction of implicit information in biosignals,” published in Methods of Information in Medicine, 332, 1997. However, Lu et al. did not show determining the three dimensional activation sequence throughout the myocardial volume, did not show determining the three dimensional distribution of transmembrane potentials or electrical potentials within the myocardial volume, did not show determining the three dimensional distribution of current dipole or monopole sources within the myocardial volume.
However, in the prior art, no descriptions have been given on imaging cardiac electric source distribution within the three dimensional space of the heart using weighted minimum norm approaches. No descriptions have been given to estimate and image the activation patterns in the three dimensional myocardium. Further innovation in the three-dimensional cardiac electrical source imaging and in three-dimensional cardiac activation imaging is much needed.
Similarly, in the prior art, no descriptions have been given on estimating activation sequence within the brain by incorporating a three dimensional brain activation model into the inverse process. Innovation in the three dimensional brain imaging by using an activation model will advance state of the art in brain source imaging.